Data Science (BS)

Program Overview

This Bachelor of Science in Data Science program provides a comprehensive understanding of data science fundamentals, including statistics, mathematics, computer science, and analytics. It prepares students for professional employment as data scientists or further graduate education. The program emphasizes data privacy, security, and ethics, and culminates in a capstone project where students apply their knowledge to real-world data science problems.

Program Outline

Degree Overview:

• Provides a detailed understanding of the core knowledge required in the field of data science, with a focus on statistics, mathematics, computer science, and analytics.
• Prepares students for both professional employment as a data scientist and further graduate education.

Outline:

Course Sequence:

Foundation Courses:

• COSC 1550 Computer Programming I (3 hours):
Covers fundamentals of computer programming and problem-solving techniques using C++.
• CSIS 1700 Data Exploration (3 hours):
Introduces principles of data visualization, data cleaning, and data exploration using statistical software packages such as R.
• COSC 1800 Python Programming (3 hours):
Develops skills in programming using Python, focusing on data analysis and manipulation tasks.

Mathematics and Statistics Courses:

• MATH 1610 Calculus I (5 hours):
Provides a solid foundation in differential calculus.
• MATH 1620 Calculus II (5 hours):
Covers integral calculus and its applications.
• MATH 2200 Statistics (3 hours):
Introduces fundamental statistical concepts and techniques for data analysis.
• MATH 2410 Discrete Mathematics (3 hours):
Explores discrete structures, logic, and combinatorics, which are essential for computer science and data analysis.

Introduction to Data Science:

• CSIS 2500 Introductions to Data Science (3 hours):
Offers a broad overview of the data science field, its methods, and applications.

Data Privacy, Security, and Ethics:

• CSIS 2700 Data Privacy, Security, and Ethics (3 hours):
Emphasizes the importance of data privacy, security, and ethical considerations in data handling.

Advanced Mathematics and Data Structures:

• MATH 3160 Linear Algebra (3 hours):
Covers vector spaces, linear transformations, and matrix theory, providing a strong foundation for data analysis algorithms.

Data Analytics Tools:

• CSIS 3300 R Programming for Data Analytics (3 hours):
Delves deeper into data analysis and visualization techniques using R.

Data Analysis Techniques:

• CSIS 3410 Information Analysis (3 hours):
Focuses on data preparation, statistical modeling, and predictive analytics.

Data Science Methods and Techniques:

• MATH 3610 Probability (3 hours):
Covers probability theory and its applications in data analysis and modeling.
• CSIS 3700 Data Analytics Methods (3 hours):
Provides practical experience in applying data science techniques to real-world problems.
• CSIS 4300 Database Systems (3 hours):
Explores the concepts, design, and implementation of database management systems.
• COSC 4310 Database Programming (3 hours):
Focuses on developing and managing databases using programming techniques.
• CSIS 4330 Data Mining (3 hours):
Covers techniques for extracting knowledge and insights from large datasets.

Data Science Capstone Project:

• CSIS 3800 Machine Learning (3 hours):
Introduces supervised and unsupervised machine learning algorithms.
• CSIS 4500 Data Science Capstone (3 hours):
Provides an opportunity for students to apply their knowledge and skills to a real-world data science project.

Assessment:

• Coursework: Includes a combination of exams, quizzes, projects, and assignments that assess students' understanding of course material.
• Capstone Project: A culminating experience that requires students to apply their learning to a significant data science problem.

Teaching:

• The program is taught by experienced faculty in data science, mathematics, computer science, and statistics.
• Courses use a mix of lectures, discussions, hands-on exercises, and group projects to provide students with a well-rounded learning experience.

Careers:

Graduates with a Bachelor of Science in Data Science can pursue various career paths, including:

• Data scientist
• Data analyst
• Machine learning engineer
• Business intelligence analyst
• Statistician